class_docstr: Class to manage a scheduled (framework-dependent) tensor variable.
  
  Uses the PiecewiseSchedule (for maximum configuration flexibility)
docstr: Returns the current value (as a tensor variable).
  
  This method should be used in loss functions of other (in-graph) places
  where the current value is needed.
  
  Returns:
      The tensor variable (holding the current value to be used).
docstr_tok: ["Returns","the","current","value","(","as","a","tensor","variable",")",".","This","method","should","be","used","in","loss","functions","of","other","(","in-graph",")","places","where","the","current","value","is","needed",".","Returns",":","The","tensor","variable","(","holding","the","current","value","to","be","used",")","."]
code: def get_current_value(self) -> TensorType:
      """Returns the current value (as a tensor variable).
  
      This method should be used in loss functions of other (in-graph) places
      where the current value is needed.
  
      Returns:
          The tensor variable (holding the current value to be used).
      """
      return self._curr_value
  
file_path: ray/python/ray/rllib/utils/schedules/scheduler.py
imports: from typing import Optional
  from ray.rllib.utils.framework import try_import_tf, try_import_torch
  from ray.rllib.utils.schedules.piecewise_schedule import PiecewiseSchedule
  from ray.rllib.utils.typing import LearningRateOrSchedule, TensorType
label_desc: Use image node_id 3 for calling the Scheduler obj's underlying member method code with example usage: obj.get_current_value() and returns: self